OpenSearch Neural Search example. Load BERT to OpenSearch and create embeddings as data is indexed. Use the embedding to preform vector search
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Updated
Jul 1, 2024
OpenSearch Neural Search example. Load BERT to OpenSearch and create embeddings as data is indexed. Use the embedding to preform vector search
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
MTEB: Massive Text Embedding Benchmark
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.
Official Weaviate TypeScript Client
PostgreSQL vector database extension for building AI applications
UI widget for adding semantic search to your React UI in just a few lines of code
A pure Python-implemented, lightweight, server-optional, multi-end compatible, vector database deployable locally or remotely.
Represent, send, store and search multimodal data
☁️ Build multimodal AI applications with cloud-native stack
The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
Elasticsearch plugin for nearest neighbor search. Store vectors and run similarity search using exact and approximate algorithms.
Epsilla is a high performance Vector Database Management System. Try out hosted Epsilla at https://cloud.epsilla.com/
Neural Search
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Official Python SDK for Kern AI refinery.
The prime repository for state-of-the-art Multilingual Question Answering research and development.
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